The Automated Screening Working Groups is a group of software engineers and biologists passionate about improving scientific manuscripts on a large scale. Our members have created tools that check for common problems in scientific manuscripts, including information needed to improve transparency and reproducibility. We have combined our tools into a single pipeline, called ScreenIT. We're currently using our tools to screen COVID preprints.
Latest preprint reviews
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A shorter symptom onset to remdesivir treatment (SORT) interval is associated with a lower mortality in moderate-to-severe COVID-19: A real-world analysis
This article has 4 authors:Reviewed by ScreenIT
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One Study of COVID-19 Spreading at The United States - Brazil - Colombia
This article has 5 authors:Reviewed by ScreenIT
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Covid-19 Prediction in USA using modified SIR derived model
This article has 1 author:Reviewed by ScreenIT
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Maraviroc inhibits SARS-CoV-2 multiplication and s-protein mediated cell fusion in cell culture
This article has 11 authors:Reviewed by ScreenIT
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Hydroxychloroquine application is associated with a decreased mortality in critically ill patients with COVID-19
This article has 8 authors:Reviewed by ScreenIT
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Increased circulating levels of angiotensin-(1–7) in severely ill COVID-19 patients
This article has 17 authors:Reviewed by ScreenIT
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Safety and Efficacy of the combined use of ivermectin, dexamethasone, enoxaparin and aspirin against COVID 19
This article has 3 authors:Reviewed by ScreenIT
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Circulating markers of angiogenesis and endotheliopathy in COVID‐19
This article has 18 authors:Reviewed by ScreenIT
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Modeling an epidemic in an imaginary small town
This article has 1 author:Reviewed by ScreenIT
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SARS-CoV-2 infections in people with primary ciliary dyskinesia: neither frequent, nor particularly severe
This article has 9 authors:Reviewed by ScreenIT